research-article

Visual complexity of chinese ink paintings

Authors:

Kang ZhangAuthors Info & Claims

SAP '17: Proceedings of the ACM Symposium on Applied Perception

Article No.: 9, Pages 1 - 8

https://doi.org/10.1145/3119881.3119883

Published: 16 September 2017 Publication History

Abstract

Complexity is a key factor influencing aesthetic judgment of artworks. Using a well-known artist Wu Guanzhong's paintings as examples, we provide quantified methods to gauge three visual attributes which influence the complexity of paintings, i.e. color richness, stroke thickness and white space. By conducting regression analysis, our research validates the influences of given visual attributes on perceived complexity, and distinguishes the complexity measurements for abstract paintings and representational paintings. Specifically, all three factors influence the complexity of abstract paintings; In contrast, mere white space influences that of representational paintings.

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Cited By

Zhang YDang RLi YMeng X(2024)A Comparative Study of Early and Late Painting Styles in Zhang Daqian’s Lotus WorksIEEE Access10.1109/ACCESS.2024.340441512(73676-73690)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3404415
Zhang WZhang JWong KWang YFeng YWang LChen W(2024)Computational Approaches for Traditional Chinese Painting: From the “Six Principles of Painting” PerspectiveJournal of Computer Science and Technology10.1007/s11390-024-3408-x39:2(269-285)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s11390-024-3408-x
Feng TZhai YYang JLiang JFan DZhang JShao LTao D(2022)IC9600: A Benchmark Dataset for Automatic Image Complexity AssessmentIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.3232328(1-17)Online publication date: 2022
https://doi.org/10.1109/TPAMI.2022.3232328
Show More Cited By

Index Terms

Visual complexity of chinese ink paintings
1. Applied computing
  1. Arts and humanities
    1. Fine arts

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Published In

cover image ACM Conferences

SAP '17: Proceedings of the ACM Symposium on Applied Perception

September 2017

101 pages

ISBN:9781450351485

DOI:10.1145/3119881

Conference Chairs:
Douglas W. Cunningham
Brandenburg University of Technology
,
Michael Breuß
Brandenburg University of Technology
,
Editor:
Stephen N. Spencer
University of Washington
,
Program Chairs:
Sophie Joerg
Clemson University
,
Victoria Interrante
University of Minnesota

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 September 2017

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Funding Sources

National NSFC project
National High-tech R&D Program

Conference

SAP '17

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SIGGRAPH

SAP '17: ACM Symposium on Applied Perception 2017

September 16 - 17, 2017

Cottbus, Germany

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Overall Acceptance Rate 43 of 94 submissions, 46%

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Citations

Cited By

Zhang YDang RLi YMeng X(2024)A Comparative Study of Early and Late Painting Styles in Zhang Daqian’s Lotus WorksIEEE Access10.1109/ACCESS.2024.340441512(73676-73690)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3404415
Zhang WZhang JWong KWang YFeng YWang LChen W(2024)Computational Approaches for Traditional Chinese Painting: From the “Six Principles of Painting” PerspectiveJournal of Computer Science and Technology10.1007/s11390-024-3408-x39:2(269-285)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s11390-024-3408-x
Feng TZhai YYang JLiang JFan DZhang JShao LTao D(2022)IC9600: A Benchmark Dataset for Automatic Image Complexity AssessmentIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2022.3232328(1-17)Online publication date: 2022
https://doi.org/10.1109/TPAMI.2022.3232328
Han KYou WShi SDeng HSun L(2022)The Doctrine of the Mean: Chinese Calligraphy with Moderate Visual Complexity Elicits High Aesthetic PreferenceInternational Journal of Human–Computer Interaction10.1080/10447318.2022.214486440:6(1355-1368)Online publication date: 17-Nov-2022
https://doi.org/10.1080/10447318.2022.2144864
Shi BGuo JWang CSu YDi YAbouOmar M(2022)Research on the visual image-based complexity perception method of autonomous navigation scenes for unmanned surface vehiclesScientific Reports10.1038/s41598-022-14355-y12:1Online publication date: 20-Jun-2022
https://doi.org/10.1038/s41598-022-14355-y
Fan ZZhu YMarković SZhang K(2022)A comparative study of oil paintings and Chinese ink paintings on compositionThe Visual Computer10.1007/s00371-022-02408-2Online publication date: 19-Feb-2022
https://doi.org/10.1007/s00371-022-02408-2
Chang RHuang Y(2021)Towards AI Aesthetics: Human-AI Collaboration in Creating Chinese Landscape PaintingCulture and Computing. Interactive Cultural Heritage and Arts10.1007/978-3-030-77411-0_15(213-224)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-77411-0_15
Qiao LGuo XLi W(2021)Classification of Chinese and Western Painting Images Based on Brushstrokes FeatureEntertainment Computing – ICEC 202010.1007/978-3-030-65736-9_30(325-337)Online publication date: 5-Jan-2021
https://doi.org/10.1007/978-3-030-65736-9_30
Fan ZZhang K(2020)Visual order of Chinese ink paintingsVisual Computing for Industry, Biomedicine, and Art10.1186/s42492-020-00059-53:1Online publication date: 12-Oct-2020
https://doi.org/10.1186/s42492-020-00059-5
Lyu RMei LXing HMeng L(2020)Research on the Perception of Calligraphy Time Sequence Based on Markov ChainProceedings of the 2nd World Symposium on Software Engineering10.1145/3425329.3425342(66-71)Online publication date: 25-Sep-2020
https://dl.acm.org/doi/10.1145/3425329.3425342
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